EB5205 Clinical Health Analytics

Module 1.1: Introduction to Health

PhD, Biomedical Engineering from NUS Faculty of Engineering, Singapore, in 2015. Research Interests: Artificial Organs, Medical Devices Design, Soft Robotics and Optimization. Joined ISS in 2016 June.Some Photos of My Life About the Course ONE week of E-learning on final week (Week 5) Consisting of a Lecture in the morning and Tutorial in the Afternoon Class information, lectures and materials can be found on IVLE. Do not email me questions, instead post it on the IVLE module forum so that we can all learn.

Patients provided with personal health tablet, a weighing

Parameters are uploaded into the system daily for monitoring

They are health monitoring

technologies that are worn or integrated into wearables

Can come in the form of a

watch, headband, shoe and many moreSmart Wearables Three layers mechanism

Cloud layer- analyze data and give user outcome Connectivity and control layer shift from smart phones to the wrist Battery life is the basic layer for small interfaces that are placed close to bodySmart Wearables Three layers mechanism

Not yet Cloud layer- attained analyze data and give user outcome at the moment Connectivity and control layer shift from smart phones to the wrist Battery life is the basic layer for small interfaces that are placed close to body Smart Wearables Benefits

Continuous health monitoring ( good for patients susceptible to sudden

health attacks)

Allows users to track and make improvements to life style

Can sync with telehealth to provide remote monitoring of patients

Seamlessly integrated into daily living

Smart Wearables Current Findings

Consumers have not fully health monitoring wearable technologies.

Most consumers do not want to pay for their device and rather be paid to use them.

Few consumers are interested in sharing health data

Consumers are concerned about privacy of their data and are sceptical of the data usage.Smart Wearables EEG-based ( My project)

Users are more motivated to achieve their health goals through

Reaping double benefits of fun and beneficial

Measuring effect: Two different users playing the same game might have different experience and tastes. Selection bias in data collection

Quality of games: Difficult to design a good game of an adequate addictive nature

Intrinsic vs extrinsic motivator:

Games may only provide temporary extrinsic motivation and effect will wear off after novelty is goneHealth Gamification Local Case Study 1

Pokemon GO

Users are motivated to

travel on foot to different regions of the country to catch Pokemon

Sign up of more than

100 million users Smart Wearables Local Case study 1

Virtual reality game designed

by Tan Tock Seng Hospital

Staff navigate a 3D virtual

hospital to identify diseases and use the right protective equipment

Another app for rehabilitation

of brain injuries survivors E-Health Cloud- What is it?

E-Health Cloud is defined as a systematic collection of electronic

health info about individual patients or populations.

It is a record in digital format and has the potential of being

shared across different health care settings

Contains a range of data like demographics, medical history,

medicationsetcE-Health Cloud Limitations of currentsystems

Costly to maintain

Fragmentation of data storage systems and insufficient exchange

of patients data between hospitals and clinics

Lack of regulation and law governing the use and protection of

patients data.E-Health Cloud-Benefits

Unified patient medical record database

Reduced cost due to sharing of overhead costs amongst

participants

Overcome shortage of IT infrastructure

Support research, national security and strategic planning

E-Health Cloud-Risks

Data security risks

Loss of data

Risks of server and system unavailability during

maintenance E-Health Cloud-Local Case Study

H-Cloud or Health Cloud is a consolidated and virtualized data centre

to host all mission critical systems for all public hospitals in SG

Developed and supported by IHiS (Intergrated Health Information

System)

Consolidates all the data centres in all hospitals in SG into a single

hub

Won the prestigious DataCloud Enterprise Cloud Award in Monaco

in 2 Jun 2015Future of Digital Healthcare (1)

Augmented reality of patients

Allows doctor to quickly access

history of walk in patients

Plastic surgery planning

Future of Digital Healthcare (2)

Retinal scans

Storage and retrieval of records using

patients retina

Prognosis and diagnosis using retina

scans Future of Digital Healthcare (3)

E-tattoo

On board solar-panel supply

Measures hydration, heart rate,

glucose levels and activity levels.

2D flexible circuit

Seamless integration with user

Role of Big Data in Health Analytics Definition of Big Data A collection of large and complex data sets which are difficult to process using common database management tools or traditional data processing applications.

Big data refers to the tools, processes

and procedures allowing an organization to create, manipulate, and manage very large data sets and storage facilities

The challenges include capturing, storing,

More incentives to professionals/hospitals to use EHR technology.

Additional Data Sources

Development of new technologies such as capturing devices, sensors, and mobile applications. Collection of genomic information became cheaper. Patient social communications in digital forms are increasing. More medical knowledge/discoveries are being accumulated. Big Data Challenges in Healthcare Inferring knowledge from complex heterogeneous patient sources. Leveraging the patient/data correlations in longitudinal records. Understanding unstructured clinical notes in the right context. Efficiently handling large volumes of medical imaging data and extracting potentially useful information and biomarkers. Analyzing genomic data is a computationally intensive task and combining with standard clinical data adds additional layers of complexity. Capturing the patients behavioral data through several sensors; their various social interactions and communications.Goals of Big Data Analytics in Healthcare

Take advantage of the massive amounts of data and provide right

intervention to the right patient at the right time. Personalized care to the patient. Potentially benefit all the components of a healthcare system i.e., provider, payer, patient, and management.Analytics PlatformEnd of Module 1.1